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Record W2765103953 · doi:10.1080/17429145.2017.1392627

Molecular response of gall induction by aphid<i>Schlechtendalia chinensis</i>(Bell) attack on<i>Rhus chinensis</i>Mill

2017· article· en· W2765103953 on OpenAlexaff
Haiying Wang, Kai Cui, Shuxia Shao, Juan Liu, Hang Chen, Chao Wang, Haixia Wu, Zixiang Yang, Qin Lu, Kirst King‐Jones

Bibliographic record

VenueJournal of Plant Interactions · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsGallAphidBiologyBotanyTranscriptomeSecondary metabolismPlant hormoneGeneHorticultureBiosynthesisGene expressionGenetics

Abstract

fetched live from OpenAlex

Horned gall is named after its shape of irregular diamond, and is induced by the fluid-feeding aphid Schlechtendalia chinensis (Bell) attacks on the leaflets that are located in the branchlets of Rhus chinensis Mill., which is enriched in gallotannin and can be widely used in medicine and the food industry. To explain the molecular mechanism of gall development, we performed transcriptome analysis by Illumina deep sequencing and digital gene expression of four tissues, including galls, leaves that grew on the same branch as the gall taken (GL), leaves from a branch without any gall (LW), and leaves from a tree without any gall (CL). Differentially expressed genes abundantly enriched in the biosynthesis of secondary metabolites, plant–aphid interactions, and plant hormone signal transduction were highly expressed in galls compared with GL and LW. Phytohormone signal transduction, dominated by IAA and ABA, coordinates primary and secondary metabolism and thus induces gall induction and development after attack by aphids. This study provides a theoretical basis for the genetic improvement and processing of gallnut resources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.278
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations22
Published2017
Admission routes1
Has abstractyes

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